A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
Bacterial foraging oriented by particle swarm optimization strategy for PID tuning
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Hybrid GA-BF based intelligent PID controller tuning for AVR system
Applied Soft Computing
Velocity Modulated Bacterial Foraging Optimization Technique (VMBFO)
Applied Soft Computing
Brief Identification and control of open-loop unstable processes by relay methods
Automatica (Journal of IFAC)
Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm
Applied Computational Intelligence and Soft Computing
2DOF PID controller tuning for unstable systems using bacterial foraging algorithm
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
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This paper proposes a novel method to tune the I-PD controller structure for the time-delayed unstable process (TDUP) using Bacterial Foraging Optimization (BFO) algorithm. The tuning process is focussed to search the optimal controller parameters (Kp, Ki, Kd) by minimising the multiple objective performance criterion. A comparative study on various cost functions like Integral of Squared Error (ISE), Integral of Absolute Error (IAE), Integral of Time-weighted Squared Error (ITSE), and Integral of Time weighted Absolute Error (ITAE) have been attempted for a class of TDUP. A simulation study for BFO-based I-PD tuning has been done to validate the performance of the proposed method. The results show that the tuning approach is a model independent approach and provides enhanced performance for the setpoint tracking with improved time domain specifications.